Abstract

The lack of tactile feedback in robot-assisted minimally invasive surgery (RMIS) limits surgeons’ ability to palpate tissues, a critical technique for locating abnormalities such as tumors. To address this challenge, we introduce TacScope, a novel, vision-based tactile sensor leveraging the magnification properties of a spherical-surface elastomer to provide tactile feedback for advanced clinical applications. TacScope features a robust, low-cost, and easyly fabricate design, enabling seamless integration into surgical robotic setups. It reconstructs high-resolution 3D geometry from variations in particle-density distribution across its elastomer surface, requiring only a single image for calibration. The curved elastomer membrane alters particle-density distribution under contact pressures, enabling detection of both surface-level and subsurface tissue abnormalities. Unlike conventional vision-based tactile sensors, TacScope is compact and tailored for surgical devices. We validated our prototype first on rigid tissue phantoms for tumor detection and shape classification, and extended evaluation to soft-tissue phantoms under a simulated operative conditions. TacScope achieved 100% accuracy detecting artificial rigid tumors at depths up to 5 mm and over 90% accuracy classifying four tumor shapes up to 6 mm. It further achieved over 96% accuracy detecting artificial soft tumors 2 mm beneath the surface, confirming its potential for safer, more precise minimally invasive surgery.

Comments

This is the publisher PDF of Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She, Advanced Robotics Research 2025, 0, e202500117. Published CC-BY-NC-ND by Wiley , the version of record is also available at DOI 10.1002/adrr.202500117.

Keywords

miniature tactile sensor, robot-assisted minimally invasive surgery, shape reconstruction, tumor detection, vision-based tactile sensor

Date of this Version

10-15-2025

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